ph.large: Phenotype data: large data set
In grmsem: Genetic-Relationship-Matrix Structural Equation Modelling (GRMSEM)
Description
A large quad-variate data set was simulated assuming an underlying Cholesky model,
with 5000 observations per trait and high polygenicity (5,000 SNPs per genetic factor).
The data set is described in full in the vignette. Genetic and residual
covariances ar assumed to be influenced by four independent genetic factors
(A1, A2, A3 and A4, based on 5000 SNPs each) and four independent residual factors (E1, E2, E3 and E4),
respectively.
Usage
1
Format
A data frame with 5000 rows and 4 columns
- Y1
trait one
- Y2
trait two
- Y3
trait three
- Y4
trait four
grmsem documentation built on Jan. 29, 2021, 5:07 p.m.
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Description
A large quad-variate data set was simulated assuming an underlying Cholesky model, with 5000 observations per trait and high polygenicity (5,000 SNPs per genetic factor). The data set is described in full in the vignette. Genetic and residual covariances ar assumed to be influenced by four independent genetic factors (A1, A2, A3 and A4, based on 5000 SNPs each) and four independent residual factors (E1, E2, E3 and E4), respectively.
Usage
1 |
Format
A data frame with 5000 rows and 4 columns
- Y1
trait one
- Y2
trait two
- Y3
trait three
- Y4
trait four
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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